MODAL CHOICE ANALYSIS USING ENSEMBLE LEARNING METHODS

• HASEGAWA Hironobu

  秋田工業高等専門学校　環境都市工学科

• NAITO Toshiyuki

  （株）ドーコン　交通部

• ARIMURA Mikiharu

  室蘭工業大学　大学院工学研究科くらし環境系領域

• TAMURA Tohru

  室蘭工業大学　大学院工学研究科くらし環境系領域

Bibliographic Information

Other Title

• アンサンブル学習による交通機関選択モデルの構築とその評価
• アンサンブル ガクシュウ ニ ヨル コウツウ キカン センタク モデル ノ コウチク ト ソノ ヒョウカ

Abstract

This study aims to determine an appropriate method for modal choice in the urban area. In our research fields, we usually use disaggregate behavioural models for modal choice analysis. The random forest method as ensemble learning technique is applied to describe the decision mechanism in the travel behaviour. As the result of this study, it is confirmed that ensemble learning method is more effective than other conventional methods.

Journal

• Journal of Japan Society of Civil Engineers, Ser. D3 (Infrastructure Planning and Management)

  Journal of Japan Society of Civil Engineers, Ser. D3 (Infrastructure Planning and Management) 68 (5), I_773-I_780, 2012

  Japan Society of Civil Engineers

Keywords

• modal choice analysis
• ensemble learning
• machine learning
• disaggregate behavioural model

Details

• CRID: 1390282680332817024
• NII Article ID: 130004559752
• DOI: 10.2208/jscejipm.68.i_773
• ISSN: 21856540
• HANDLE: 10258/00010403
• NDL BIB ID: 025240088
• Web Site: https://muroran-it.repo.nii.ac.jp/records/10464
• Web Site: http://id.ndl.go.jp/bib/025240088
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I025240088
• Text Lang: ja
• Data Source:
  • JaLC
  • IRDB
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed